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overview noao.imred.crutil



The Cosmic Ray Package: CRUTIL

The cosmic ray package provides tools for identifying and removing cosmic rays in images. The tasks are:

 cosmicrays - Remove cosmic rays using flux ratio algorithm
  craverage - Detect CRs against average and avoid objects
  crcombine - Combine multiple exposures to eliminate cosmic rays
     credit - Interactively edit cosmic rays using an image display
      crfix - Fix cosmic rays in images using cosmic ray masks
     crgrow - Grow cosmic rays in cosmic ray masks
   crmedian - Detect and replace cosmic rays with median filter
   crnebula - Detect and replace cosmic rays in nebular data

The best way to remove cosmic rays is using multiple exposures of the same field. When this is done the task crcombine is used to combine the exposures into a final single image with cosmic rays removed. The images are scaled (if necessary) to a common data level either by multiplicative scaling, an additive background offset, or some combination of both. Cosmic rays are then found as pixels which differ by some statistical amount away for the average or median of the data.

A median is the simplest way to remove cosmic rays. This is an option with crcombine . But this does not make optimal use of the data. An average of the pixels remaining after some rejection operation is better. If the noise characteristics of the data can be described by a gain and read noise then cosmic rays can be optimally rejected using the "crreject" algorithm. This works on two or more images. There are a number of other rejection algorithms which can be used as described in the task help.

The rest of the tasks in the package are used when only a single exposure is available. These include interactive editing with credit . The replacement algorithms in this task may also be used non-interactively if you have a list of pixel coordinates as input. Other tasks automatically identifying pixels which are significantly higher than surrounding pixels.

The simplest of these tasks is crmedian . This replaces cosmic rays with a median value and produces a cosmic ray mask which is a simple type of integer image where good pixels have a value of zero and bad pixels have a non-zero value. The tasks crgrow and crfix are provided to use this type of cosmic ray mask. The former will flag additional pixels within some radius of the flagged pixels in the mask. The latter is the basic tool for replacing the identified pixels in the data by neighboring data. It uses linear interpolation along lines or columns. The median task is simple but it often will flag the cores of stars or other small but real features.

The task craverage is similar to crmedian in that it compares the pixel values against a smoothed version. Instead of a median it uses an average with the central pixel excluded. It is more sophisticated in that it also compares the average against a larger median to see if the region corresponds to an object. Thus it can detect objects and the task could be used as a simple object detection task in its own right. Because the hardest part of cosmic ray detection from a single image is avoiding truncation of the cores of stars this task does not allow cosmic rays to be detected where it thinks there is an object. This task is also more versatile in allow separate mask values and works on a list of images.

Somewhat more sophisticated algorithms are available in the tasks cosmicrays and crnebula . These attempt to determine if a deviant pixel is the core of a star or part of a linear nebular feature respectively.

The best use of these tasks is to experiment and iterate. In particular, one may want to iterate a task several times and use both cosmicrays and craverage .

Good hunting!


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